Abstract
INTRODUCTION: Identification of hospitalized patients with suddenly unfavorable clinical course remains challenging. Models using objective data elements from the electronic health record may miss important sources of information available to nurses. METHODS: We recorded nurses' perception of patient potential for deterioration in 2 medical and 2 surgical adult hospital units using a 5-point score at the start of the shift (the Worry Factor [WF]), and any time a change or an increase was noted by the nurse. Cases were evaluated by three reviewers. Intensive care unit (ICU) transfers were also tracked. RESULTS: 31 159 patient-shifts were recorded for 3185 unique patients during 3551 hospitalizations, with 169 total outcome events. Out of 492 potential deterioration events identified, 380 (77%) were confirmed by reviewers as true deterioration events. Likelihood ratios for ICU transfer were 17.8 (15.2-20.9) in the 24 hours following a WF > 2, and 40.4 (27.1-60.1) following a WF > 3. Accuracy rates were significantly higher in nurses with over a year of experience (68% vs 79%, P = 0.04). The area under the receiver operator characteristic curve (AUROC) was 0.92 for the prediction of ICU transfer within 24 hours. DISCUSSION: This is a higher accuracy than most published early warning scores. CONCLUSION: Nurses' pattern recognition and sense of worry can provide important information for the detection of acute physiological deterioration and should be included in the electronic medical record.